图像多角度局部特征提取及相似性匹配技术研究

On image multi-view local feature extraction and similarity matching

图像特征提取是计算机视觉应用的根本基础。研究了SIFT、LBP和HOG等3种信息互补的局部特征(即多角度局部特征)提取算法,研究了基于稀疏编码的图像相似性匹配算法,并以基于内容的图像检索(CBIR)为应用实例,验证了算法的有效性和高效性。

Image feature extraction is a fundamental basis for computer vision applications. Three complementary local features （muhi-view local features） extraction algorithms, namely SIFT, LBP, HOG, are researched, and image similarity matching algorithm based on sparse coding is studied. Content-based Image Retrieval （CBIR） is taken as the application example to verify the effectiveness and efficiency of these algorithms.